Earticle

With the development of network technology and the popularization of mobile terminals, the research and development of M-Learning resources based on iPad-user interaction technology, namely e-textbooks, has attracted increasing attention in global educative reforms. On the basis of the research on iPad’s user-machine interaction technology, this paper takes the bilingual e-textbooks development of The Kazak Alphabet as an example. It proposes basic steps and framework of the research and development and summarizes the key interaction technology and the ways of realization of preparing, developing, packaging and publishing in the hope that it can provide the foundation for the development of M-Learning and bilingual education.

Multiplier is the major component for processing of large amount of data in DSP applications. Using different recoding schemes in Fused Add-Multiply (FAM) design for the reduction of power and look up tables. The performance of 16-bit signed and unsigned multipliers were designed and obtained results are tabulated using Efficient Modified Booth Recoding (EMBR) techniques, which can be used for low power applications.

For wireless sensor networks, it is difficult to balance the energy distribution and reduce the energy consumption in the data transmission process. On the basis of the original LEACH protocol and level technique, a new method of cluster heads collection and two-level clustering transmission is proposed. By controlling the distances among the cluster heads, the uniform distribution of cluster heads is satisfied. And then using two-level mode, the data are transmitted to the base station. LEACH is compared with the improved method about the remaining energy and alive nodes. Simulation results show that the improved method can reduce the network consumption energy greatly and lengthens the network lifetime efficiently.

Privacy is an important issue in Context-aware recommender systems (CARSs). In this paper, we propose a privacy-preserving CARS in which a user can limit the contextual information submitted to the server without sacrificing a significant recommendation accuracy. Specifically, for users, we introduce a client-side algorithm that the user can employ to generalize its context to some extent, in order to protect her privacy. For the recommendation server, two server-side recommendation algorithms are proposed, which operate under the condition that only a generalized user context is given. The experimental results have shown that, using our approaches, the user context privacy can be achieved without a significant degradation of the recommendation accuracy.

Following the developments in industrial robot technology, robotics has found its way into the medical field and is used in a range of surgical disciplines. The main purpose of the use of robots is to increase the precision, quality and safety of surgical procedures. Robotics is not yet used in dentistry even though all the necessary technologies have already been developed and could easily be adapted. Some of the technologies are already used in dentistry, such as image-based simulation of implant surgery followed by the use of surgical guides, and creating digital impressions of pre parathions using an intra-oral scanner, after which a milling device produces the restoration, but we have not yet seen any robot able to prepare teeth for crowns, inlays or bridges. Such a robot would fundamentally be a dental drilling device coupled with a navigation device to determine the correct position of the device in relation to the patient. However this technique is very essential to have the minimal pain and reduce bleeding but control of these robots/joints are very complicated. This paper proposes new fuzzy type sliding mode controller for multi-DOF joints to control of motor vibration. The fuzzy (PD+I)2 single-input single-output (SISO) fuzzy system is used to control of chattering in sliding mode controller. In most research al researchers wants to eliminate the chattering but, this research focuses on chattering control. Various operation situations such as the set point control and the trajectory control are simulated. The simulation results demonstrate that the chattering and the steady state errors, which usually occur in the classical sliding mode control, are limitation control and satisfactory trajectory tracking is achieved.

Subspace outlier mining has a very important significance in big data analysis. To a large extent, subspace clustering algorithm has impact on the efficiency of mining outliers in subspaces. To solve the problem that CMI method selects best clustering subspaces unstably and complexly, formulas of chain rule of Cumulative Entropy, Cumulative Total Correlation and Cumulative Holoentropy were given. Cumulative Holoentropy was used to mine the best clustering subspaces on continuous data sets in which outliers were detected. Subspace outlier detection algorithm based on Cumulative Holoentropy was then proposed. Finally, the validity and scalability of proposed method were tested on real datasets and virtual datasets. Experiment shows that the efficiency of mining outliers in subspaces is enhanced by the proposed algorithm.

Software effort and cost estimation has turned out to be the major challenge in IT industries. In this paper, different software effort and cost estimation techniques like algorithmic methods, expert judgment, analogy based estimation and soft computing methods and their various aspects are discussed. Software effort estimation is followed by cost assessment that is useful for both customers and developers. In this paper comparison between different approaches are discussed and proposed a hybrid technique for effort estimation using fuzzy logic and neural network. This will be useful to make better estimation results.

A new channel estimation method of neural network based on complex radial basis function (CRBF) is proposed to enhance the anti-interference ability of traditional pilot frequency estimation algorithm in power line communication (PLC). This method builds up a new channel model of complex field signals in PLC. The complete response model was established by using transmitting terminal’s pilot signal as input sample data, pilot signal’s frequency response as output sample data, and pre-setting mean square error (MSE) and diffusion constant. Computer simulations show that compared with the traditional algorithm the channel estimation was more accurate and had lower MSE and bit error rate (BER).

The efficiency of perovskite materials solar cells skyrockets from 3.8% in 2009 when it is first developed in this field to 19.3% in 2014, and higher efficiency is also anticipated by researchers and merchants all over the world. Simultaneously, new kinds of LED and semiconductor laser equipments based on pervoskite are also developed with the bright future into a new era and the development treads on the heel of perovskite solar cells. In this paper the state-of-the-art and highlight progressin these related fields will be reviewed and the scientific challenges and comments on the current and future issues are mentioned.

This Paper looks at the performance of photovoltaic system in nonideal conditions that causes multiple maximum power points (MPPs) on the power-voltage (PV) characteristics curve. Since the efficiency of PV-panel is low, advanced power electronics converter are employed to improve the overall system efficiency.In this paper Solar panel is modeled and analyzed in MATLAB/SIMULINK. To get the maximum efficiency and maximum power the entire system must be linked with MPPT technique. Here Perturb & Observe and Incremental Conductance algorithms are compared on the basis of tracking capability and stability under rapidly and gradual changing weather conditions where Inc proved to be better than P&O. Pulse width modulation type DC-DC Boost converter is used for matching load impedance with PV arrays.

Relay protection and safety device are regarded as the sentry of safe and reliable operation of the power grid. It plays a very important role in the power grid, and can determine whether the normal operation of the power system. This article considers the influence of the fuzzy uncertainty of relay protection failure rate to power system on the basis of Markov model, and researches the dynamic fault tree analysis method in the case of fuzzy failure parameter. A dynamic fault model has been built. The triangular fuzzy numbers are used to express the failure rate of the components and system, after which the fuzzy Markov model has been established based on the dynamic fault tree model obtained before. The fuzzy reliability curve and fuzzy failure probability on given degree of membership could be obtained. Finally, the fuzzy Markov model based dynamic fault tree analysis method is used for reliability modeling and analysis of relay protection. The results show that this method can conduct reliability modeling and quantitative assessment effectively for systems which have dynamic failure characteristics and uncertainty of failure rate.

The combination of ampere-hour method and open-circuit voltage method in the photovoltaic measurement system is studied in this paper. In order to achieve the purpose of online measurement for remaining capacity, the influence of internal battery discharge and temperature on the battery capacity should be considered. The battery capacity decreases by the increasing charging times, and the increasing terminal voltage difference causes the inaccurate measurement of the capacity of battery. In this paper, two experimental measurement methods are employed, which are complementary to each other, to make the system measurement more accurate and extend the life of lead-acid batteries. If the charging process of photovoltaic system is unstable, an optimization of lead-acid battery applications in photovoltaic energy storage system is explored at the same time. Finally, an illustrative example is presented to demonstrate the effectiveness of the proposed measuring method.

As mobiles become cheaper and gain popularity, mobile applications are developing quickly and trying to utilize more techniques to make these applications more efficient and usable. Augmented reality is a live direct or indirect view of a physical, real-world environment whose elements are augmented (or supplemented) by computer-generated sensory input such as sound, video, graphics or GPS data. This research develops an android mobile application that utilizes real-time image processing techniques to provide simulated functionality to a hand drawing of piano keys. A piano keyboard with fourteen white keys and ten black keys is drawn used a black thick pen on paper, and the mobile is set in an angel that gives the optimum view of the piano keyboard when the camera is turned on. When the application is started, a camera shot of the piano, without the presence of hands or fingers in the view, is taken. The user can then start playing on his drawn piano. The application detects keystrokes and decides which key is pressed; and then plays the corresponding tone. The application is developed using OpenCV library which focuses on real-time image processing and computer vision, since the target devices with android platform, a Java program is used to port the C++ code to android. The application is tested on multiple android-based devices with different specifications under good lighting conditions. The empirical results are impressive and comparable across different devices, despite all changes in lighting and background; all devices exhibited the same level of accuracy in detecting fingers and drawn pianos.

Developing computer software system is a crucial part of the intelligent design. In order to solve problems presented in software system quality analysis, this paper proposes a quality analysis model for computer software system based on fuzzy information content. In this model, fuzzy information content of quality analysis indicators is defined according to information axiom, and a software system quality analysis index system is constructed with the basic layer, the support layer and the application layer considered. With the index system, fuzzy information content can be computed and analyzed to obtain fuzzy information content of computer software system. This facilitates the quantitative analysis on the quality of the software system. Finally, an engineering case study is introduced to explain how the model works and proves efficacy and feasibility of the model.

Non-linearity coupled by all of the sensors and transducers gives set to either difficulties for direct digital readout, on-chip interface, testing, calibration and control. Also, the performance of a transducer is affected adversely by variations in working environments over them. Under the sovereignty of ANN based transducer modeling, the use of single layer ANN has been proposed in two separate studies with quite affluent results. The first existing model is based on the architecture of an adaptive linear (ADALINE) network trained with Widrow-Hoff’s learning algorithm. The other is based on the concept of Functional Link Artificial Neural Network (FLANN) designed on the architecture of a single layer linear ANN trained with Gradient-descent with momentum based learning algorithm. To have an optimal solution, it is proposed to amalgamate the direct model of the transducers using the concept of a Polynomial-ANN trained with BFGS Quasi-Newton Learning algorithm. The proposed Polynomial-ANN oriented transducer model is implemented based on the topology of a single-layer feed-forward back-propagation network. The proposed transducer modeling technique provides an extremely fast convergence speed with increased accuracy for the assessment of static input-output characteristics of the transducers and also for the solution of linearizing the non-linear transducers.

In order to improve the weak situation of the global search ability, the stability and time consuming of optimization of differential evolution(DE) algorithm in solving high dimensional optimization problem, an improved differential evolution algorithm with multi- population and multi-strategy(MPMSIDE) is proposed to solve high dimensional optimization problem. Firstly, the different DE mutation strategies are studied. Then the MPMSIDE algorithm divides the population into several sub-populations, which evolve independently and communicate with each other at regular intervals by using different DE strategies, in order to save the computation time. And the improved mutation strategy and local optimization strategy are introduced to raise and balance the global searching ability and local searching ability, and improve the optimization efficiency. The selfadaptive update strategy is used to adjust the scaling factor and crossover factor for making the parameter sensitivity of DE algorithm and improving the stability and robustness. Finally, the proposed MPMSIDE algorithm is applied to standard test function optimization for verifying the effectiveness. The experimental results show that the proposed MPMSIDE algorithm has a relatively better optimization performance for solving complex optimization problem, and takes on remarkable optimizing ability, higher searching accuracy and faster convergence speed.

In this work, a new blind separation algorithm for permuted alias image based on dictionary learning is proposed according to a type of permuted alias image with noise diversity. Sparse representation of permuted alias image is obtained by dictionary learning method, since it has high adaptability and its representation result has higher sparsity degrees than that of parameter dictionary. An optimal permuted alias image is achieved by conducting sparse representation with K-SVD dictionary learning algorithm restrained with nonzero element number. The size and the location of permuting region is found by detecting the subtraction image, which is defined as the difference between the reconstructed permuted alias image and the original permuted alias image. The permuting region is optimized by implementing image morphological operation and is separated from the permuted alias image by the threshold. Experimental results show that the permuting sub-images can be efficiently separated from the permuted alias image, which is not affected by the size, location, number of permuting sub-images and noise level of the permuting sub-images.

In Digital systems like digital signal processors, FIR filters and micro processors etc, Multiplier is one of the key hardware blocks. The performance of the overall system is determined by the multiplier performance because the multiplier is generally the slowest element in the whole system and also it is occupying more area. In the multiplier, we use adder circuit repeatedly. So, an efficient adder circuit will be used in multipliers, it gives better performance. In the proposed work, new Carry Select Adders (CSLA) are replaced to enhance the multiplier performance. Carry Select Adder (CSLA) provides better performance with respect to speed and area. Previously, a binary to excess one converter (BEC) based Square Root Carry Select Adder is designed but in that data dependency is very high, it gives some speed penalty. An efficient CSLA design is obtained using improved logic units to eradicate the data dependency and redundant logic operations. In this proposed work, the intended efficient Square Root Carry Select Adder is compared with BEC based CSLA of respective architectures, after having comparison the proposed CSLA is efficient with respective to area and delay is used in Multiplier design. This work gives better results regarding to the performance parameters such as delay and area of designed multiplier using new efficient square root carry select adder compared to BEC based CSLA multiplier.

Semantic similarity computation is of great importance in many applications such as natural language processing, knowledge acquisition and information retrieval. In recent years, many concept similarity measures have been developed for ontology and lexical taxonomy. Generally speaking, ontology concepts semantic similarity computation is tedious and time-consuming. This paper puts forward an optimization algorithm to simplify semantic similarity computation. The optimization algorithm utilizes hierarchical relationship between concepts to simplify similarity computation process. Simulation experiments showed the optimization algorithm could make similarity computation simple and convenient, and similarity computation speed was improved by one time. The more complexity an ontology structure, and the bigger the maximum depth of ontology, the more significantly the performance improved.

Plentiful algorithms for identifying digital straight segment (DSS) are presented in literatures, but few mention how to indicate detected results in a visual-pleasure presentation. This paper proposed an algorithm for rendering tangential frames, i.e., edges of tangential covers overlapping detected DSS. The algorithm adapts strategies as linear regression and coordinate rotation to estimate points of frame. The implementation based on these strategies is surprisingly intuitive. The visual results of algorithm are shown and computational costs with respect to data of different dimensions are analyzed. The experimental results show proposed algorithm possesses a nearly linear time and its renderings are correct and visually-attractive.

In this paper, we present two comparisons in isolated printed Tifinagh characters recognition, in fact the first comparison is between four hybrid methods exploited in features extraction which are the retinal coding combined with the Hu then with Legendre then with Zernike invariant moments, finally with these tree moments at the same time; in contrast the second comparison is performed in order to deduce what is the most powerful between both kernel functions used in the support vectors machines classifier. For this purpose we have used for pre-processing each character image the median filter, the thresholding, the normalization, the thinning, the centering and the skeletonization techniques. Furthermore, the experiments results that we have obtained demonstrates really that the most powerful hybrid method is that combines between retinal coding and all tree invariant moments concerning features extraction while the Gaussian kernel is more performant than that polynomial concerning classification.

First, we describe some properties of the masonry structures. It is an urgent task to ensure the safety of the masonry structure by using information technology to monitor the instantaneous deformation dynamically and find out clues of potential hazard real time. This essay gives an empirical research with three-dimensional motion parallax (3-DMP) to this problem, besides; the grey theory model is used to analyze the deformation. The Artificial Earthquake Motional Model （AEM）and the developed software for static and dynamic analyses of different types of masonry structures are illustrated. The combination of multi-technology methods can overcome the error, and play an important role in improving the safety and reliability of the masonry structure. With the analyzed and processed data from digital cameras effectively, we get a precision result approximately equal 2.1‰

In this paper, the problem of delay-dependent absolute stability condition for a new class of Takagi-Sugeno (T-S) fuzzy Lurie control systems with time-varying delay is investigated. New Lyapunov functions are defined by utilizing the Lyapunov-Krasovskii functional (LKF). Meanwhile, free-weighting matrix method and some techniques are used to obtain a new absolute stability condition, which is different from previous research. Finally, a numerical example will be provided to demonstrate feasibility and less conservativeness of the proposed result.

The goal of DMAIC approach is to reduce the variation in output result by business process improvement. DMAIC of “6 σ” methodologies can be implemented in software development life cycle (SDLC) to be competitive in the market by making the focus to customer satisfaction. Implementing “6 σ” in every smallest section of SDLC will give enough value addition to the organization towards achieving customer-based quality. This paper will describe the implementation of “6 σ” tool in the testing process; improvements of customer satisfaction and project cost effectiveness. Here we will be measuring the variation of testing metrics, control of the variation and how it affects the post release defects using QFD and regression analysis.

In the paper, approximate ready trace equivalence for differential semi-algebraic hybrid system is proposed. The equivalence can be used to optimize differential semialgebraic hybrid system. The Concept is proposed on the basis of concrete process algebra and numerical analysis theory. In the approximate ready trace equivalence definition, we consider a cut operator for a polynomial and partial approximation for polynomial. Then we get a strict equivalence between two polynomials. Its advantage is that the new polynomial approximation method overcomes the drawback that traditional approximation method is not transitive, which can be used for automatic reasoning. In order to judge the two differential semi-algebraic hybrid system is equivalent, the axiom system for the approximate ready trace equivalence of differential semi-algebraic hybrid system is presented. This axiom system is a complete axiom system.

As for heavy traffic, road congestion and the hard extraction of vehicles in dynamic video, an improved method of dynamic video background updating is proposed. By using frame-to-frame differences and mask technology, the hole of difference image is eliminated, then extracts the reliably initial background. The image is segmented by using double threshold based on the combination of Bacterial Foraging Optimization Algorithm and Otsu Algorithm to improve the effect and reliability of background updating. Experiments shows that it is an effective way that is good in speed and effective in background extraction, and provides a good foundation for further study of the vehicle tracking.

Traditional flexible flow shop scheduling cannot adapt to the work processes with existence of parallel machines, and blocks or limits the processes with no-wait constraints. Firstly, according to the problem in NWBFFSSP, which minimizes the maximum time used in the flow shop, an optimal solving model has been designed to realize the flexible flow shop scheduling with multi constraints; besides, for the distribution of machinery is improved, Finally, in the solving process, a real-time release priority strategy has been proposed to determine processing machine for each work piece. Furthermore, a methodology to detect work piece conflicts has been introduced while the conflicts are then eliminated by a kind of right moving strategy based on the maximum difference. The experimental results verify the effectiveness and feasibility of the proposed algorithm.

During the iteration process, the traditional K-means algorithm is easily fall into local optimal solution. In order to solve this problem, this paper proposed an improved Kmeans algorithm, and used the method of maximum distance equal division to select the initial cluster centers. We preset k cluster centers, and avoid it falling into local optimal solution. Apply this improved algorithm into e-commerce customer loyalty analysis, this paper put forward a customer loyalty analysis model using the parameters of shopping recency, shopping frequency, shopping monetary, customer satisfaction and customer attention, and used the improved K-means algorithm to analyze the RFMSA customer loyalty model. The studies show that the improved K-means algorithm and RFMSA model can effectively divide the loyalty of the e-commerce customer, it also can fully reflect the customer’s current value and potential value-added ability, and provide the basis that the e-commercial enterprises can adopt different marketing strategies for different target customers.

Performance analysis of process plays a significant role in improving the overall efficiency of any system. Usually, this task is accomplished either by system level commands or user space applications, based on procfs or sysfs file system. There are many creative techniques and popular commercial applications available to perform this management and fine tuning of process. But, these existing user space based mechanisms are limited in scope and often fail to provide the required process specific data to user. In order to avoid this limitation, we have proposed a new linux kernel module (LKM) based approach, which can be potentially used to track any process specific data in real time. In this approach, the user does not require any separate tool but the kernel module to gather all essential information. Further, the competence of this module based technique can be enhanced by incorporating additional functionalities and thereby making it a full-fledged multi process abstraction layer to cater the needs of any high performance embedded platform.

Enhancing the development competitiveness holds significance to the sustainable development of tourism cities. It is complex system engineering as the development competitiveness of tourism cities is influenced by many factors. Therefore, this paper studies the development competitiveness from ten dimensions, namely ecological factor, environmental factor, cultural factor, educational factor, scientific factor, civilizational factor, brand factor, economic factor, market factor and development potential factor. A multi-attribute evaluation model of the development competitiveness of tourism cities is established based on grey clustering analysis. Through the study of influence factors, grey clustering analysis function is established to obtain the grey clustering coefficient. Given that influence factors are distinct in terms of importance, the weighted grey clustering analysis model is established for the evaluation of development competitiveness of tourism cities. Finally, a case is studied to verify the model.